Realistic CT data augmentation for accurate deep-learning based segmentation of head and neck tumors in kV images acquired during radiation therapy.

BACKGROUND: Using radiation therapy (RT) to treat head and neck (H&N) cancers requires precise targeting of the tumor to avoid damaging the surrounding healthy organs. Immobilisation masks and planning target volume margins are used to attempt to mitigate patient motion during treatment, however patient motion can still occur. Patient motion during RT can lead to decreased treatment effectiveness and a higher chance of treatment related side effects. Tracking tumor motion would enable motion compensation during RT, leading to more accurate dose delivery. PURPOSE: The purpose of this paper is to develop a method to detect and segment the tumor in kV images acquired during RT. Unlike previous tumor segmentation methods for kV images, in this paper, a process for generating realistic and synthetic CT deformations was developed to augment the training data and make the segmentation method robust to patient motion. Detecting the tumor in 2D kV images is a necessary step toward 3D tracking of the tumor position during treatment. METHOD: In this paper, a conditional generative adversarial network (cGAN) is presented that can detect and segment the gross tumor volume (GTV) in kV images acquired during H&N RT. Retrospective data from 15 H&N cancer patients obtained from the Cancer Imaging Archive were used to train and test patient-specific cGANs. The training data consisted of digitally reconstructed radiographs (DRRs) generated from each patient's planning CT and contoured GTV. Training data was augmented by using synthetically deformed CTs to generate additional DRRs (in total 39 600 DRRs per patient or 25 200 DRRs for nasopharyngeal patients) containing realistic patient motion. The method for deforming the CTs was a novel deformation method based on simulating head rotation and internal tumor motion. The testing dataset consisted of 1080 DRRs for each patient, obtained by deforming the planning CT and GTV at different magnitudes to the training data. The accuracy of the generated segmentations was evaluated by measuring the segmentation centroid error, Dice similarity coefficient (DSC) and mean surface distance (MSD). This paper evaluated the hypothesis that when patient motion occurs, using a cGAN to segment the GTV would create a more accurate segmentation than no-tracking segmentations from the original contoured GTV, the current standard-of-care. This hypothesis was tested using the 1-tailed Mann-Whitney U-test. RESULTS: The magnitude of our cGAN segmentation centroid error was (mean ± standard deviation) 1.1 ± 0.8 mm and the DSC and MSD values were 0.90 ± 0.03 and 1.6 ± 0.5 mm, respectively. Our cGAN segmentation method reduced the segmentation centroid error (p < 0.001), and MSD (p = 0.031) when compared to the no-tracking segmentation, but did not significantly increase the DSC (p = 0.294). CONCLUSIONS: The accuracy of our cGAN segmentation method demonstrates the feasibility of this method for H&N cancer patients during RT. Accurate tumor segmentation of H&N tumors would allow for intrafraction monitoring methods to compensate for tumor motion during treatment, ensuring more accurate dose delivery and enabling better H&N cancer patient outcomes.

The MANGO study: a prospective investigation of oxygen enhanced and blood-oxygen level dependent MRI as imaging biomarkers of hypoxia in glioblastoma.

Background: Glioblastoma (GBM) is the most aggressive type of brain cancer, with a 5-year survival rate of ~5% and most tumours recurring locally within months of first-line treatment. Hypoxia is associated with worse clinical outcomes in GBM, as it leads to localized resistance to radiotherapy and subsequent tumour recurrence. Current standard of care treatment does not account for tumour hypoxia, due to the challenges of mapping tumour hypoxia in routine clinical practice. In this clinical study, we aim to investigate the role of oxygen enhanced (OE) and blood-oxygen level dependent (BOLD) MRI as non-invasive imaging biomarkers of hypoxia in GBM, and to evaluate their potential role in dose-painting radiotherapy planning and treatment response assessment. Methods: The primary endpoint is to evaluate the quantitative and spatial correlation between OE and BOLD MRI measurements and [18F]MISO values of uptake in the tumour. The secondary endpoints are to evaluate the repeatability of MRI biomarkers of hypoxia in a test-retest study, to estimate the potential clinical benefits of using MRI biomarkers of hypoxia to guide dose-painting radiotherapy, and to evaluate the ability of MRI biomarkers of hypoxia to assess treatment response. Twenty newly diagnosed GBM patients will be enrolled in this study. Patients will undergo standard of care treatment while receiving additional OE/BOLD MRI and [18F]MISO PET scans at several timepoints during treatment. The ability of OE/BOLD MRI to map hypoxic tumour regions will be evaluated by assessing spatial and quantitative correlations with areas of hypoxic tumour identified via [18F]MISO PET imaging. Discussion: MANGO (Magnetic resonance imaging of hypoxia for radiation treatment guidance in glioblastoma multiforme) is a diagnostic/prognostic study investigating the role of imaging biomarkers of hypoxia in GBM management. The study will generate a large amount of longitudinal multimodal MRI and PET imaging data that could be used to unveil dynamic changes in tumour physiology that currently limit treatment efficacy, thereby providing a means to develop more effective and personalised treatments.

MArkerless image Guidance using Intrafraction Kilovoltage x-ray imaging (MAGIK): study protocol for a phase I interventional study for lung cancer radiotherapy.

INTRODUCTION: In radiotherapy, tumour tracking leads the radiation beam to accurately target the tumour while it moves in a complex and unpredictable way due to respiration. Several tumour tracking techniques require the implantation of fiducial markers around the tumour, a procedure that involves unnecessary risks and costs. Markerless tumour tracking (MTT) negates the need for implanted markers, potentially enabling accurate and optimal radiotherapy in a non-invasive way. METHODS AND ANALYSIS: We will perform a phase I interventional trial called MArkerless image Guidance using Intrafraction Kilovoltage x-ray imaging (MAGIK) to investigate the technical feasibility of the MTT technology developed at the University of Sydney (sponsor). 30 participants will undergo the current standard of care lung stereotactic ablative radiation therapy, with the exception that kilovoltage X-ray images will be acquired continuously during treatment delivery to enable MTT. If MTT indicates that the mean lung tumour position has shifted >3 mm, a warning message will be displayed to indicate the need for a treatment intervention. The radiation therapist will then pause the treatment, shift the treatment couch to account for the shift in tumour position and resume the treatment. Participants will be implanted with fiducial markers, which act as the ground truth for evaluating the accuracy of MTT. MTT is considered feasible if the tracking accuracy is <3 mm in each dimension for >80% of the treatment time. ETHICS AND DISSEMINATION: The MAGIK trial has received ethical approval from The Alfred Human Research Ethics Committee and has been registered with ClinicalTrials.gov with the Identifier: NCT04086082. Estimated time of first recruitment is early 2022. The study recruitment and data analysis phases will be performed concurrently. Treatment for all 30 participants is expected to be completed within 2 years and participant follow-up within a total duration of 7 years. Findings will be disseminated through peer-reviewed publications and conference presentations. TRIAL REGISTRATION NUMBER: NCT04086082; Pre-result.

Geriatric Assessments Can Predict Functional Outcome and Mortality after Urological Tumor Surgery.

INTRODUCTION: Older patients undergoing major urological tumor surgery are at severe risk of functional deterioration, complications, and mortality. We prospectively evaluated geriatric assessment tools and developed a novel easy-to-use assessment tool for clinical use. METHODS: In 159 patients, geriatric assessment tools were used prior to cystectomy, prostatectomy, and renal tumor surgery, and their peri- and postoperative courses were recorded. Using all the tests, a short and easy-to-use assessment tool was developed, and nomograms were generated to predict functional outcomes and mortality. RESULTS: Of all the patients, 13.8% underwent radical cystectomy, 37.7% underwent radical prostatectomy, and 48.4% underwent tumor surgery of the kidney at the age of 70 years or older. The average age was 75.6 years. Incomplete functional recovery at day 30 and day 180 was observed in 37.7% and 36.1% of the patients, respectively, and incomplete functional recovery was associated with impaired mobility, previous care dependency, frailty, comorbidities, and a high ASA score. The only predictor for high-grade complications was comorbidities, whereas mortality was associated with the geriatric screening tool scores, impaired mobility, preoperative care dependency, and comorbidities. The Erlangen Index (EI), a combination of the selected assessment tools, showed a good prediction of early (p = 0.002) and medium-term (p = 0.002) functional outcomes and mortality (p = 0.001). CONCLUSION: Our prospective evaluation confirms the high risk of incomplete functional recovery, high-grade complications, and mortality in older patients undergoing major urological tumor surgery. The EI is an easy-to-use preoperative assessment tool and therefore should be used in preoperative patient counseling.

The markerless lung target tracking AAPM Grand Challenge (MATCH) results.

PURPOSE: Lung stereotactic ablative body radiotherapy (SABR) is a radiation therapy success story with level 1 evidence demonstrating its efficacy. To provide real-time respiratory motion management for lung SABR, several commercial and preclinical markerless lung target tracking (MLTT) approaches have been developed. However, these approaches have yet to be benchmarked using a common measurement methodology. This knowledge gap motivated the MArkerless lung target Tracking CHallenge (MATCH). The aim was to localize lung targets accurately and precisely in a retrospective in silico study and a prospective experimental study. METHODS: MATCH was an American Association of Physicists in Medicine sponsored Grand Challenge. Common materials for the in silico and experimental studies were the experiment setup including an anthropomorphic thorax phantom with two targets within the lungs, and a lung SABR planning protocol. The phantom was moved rigidly with patient-measured lung target motion traces, which also acted as ground truth motion. In the retrospective in silico study a volumetric modulated arc therapy treatment was simulated and a dataset consisting of treatment planning data and intra-treatment kilovoltage (kV) and megavoltage (MV) images for four blinded lung motion traces was provided to the participants. The participants used their MLTT approach to localize the moving target based on the dataset. In the experimental study, the participants received the phantom experiment setup and five patient-measured lung motion traces. The participants used their MLTT approach to localize the moving target during an experimental SABR phantom treatment. The challenge was open to any participant, and participants could complete either one or both parts of the challenge. For both the in silico and experimental studies the MLTT results were analyzed and ranked using the prospectively defined metric of the percentage of the tracked target position being within 2 mm of the ground truth. RESULTS: A total of 30 institutions registered and 15 result submissions were received, four for the in silico study and 11 for the experimental study. The participating MLTT approaches were: Accuray CyberKnife (2), Accuray Radixact (2), BrainLab Vero, C-RAD, and preclinical MLTT (5) on a conventional linear accelerator (Varian TrueBeam). For the in silico study the percentage of the 3D tracking error within 2 mm ranged from 50% to 92%. For the experimental study, the percentage of the 3D tracking error within 2 mm ranged from 39% to 96%. CONCLUSIONS: A common methodology for measuring the accuracy of MLTT approaches has been developed and used to benchmark preclinical and commercial approaches retrospectively and prospectively. Several MLTT approaches were able to track the target with sub-millimeter accuracy and precision. The study outcome paves the way for broader clinical implementation of MLTT. MATCH is live, with datasets and analysis software being available online at https://www.aapm.org/GrandChallenge/MATCH/ to support future research.

The first prospective implementation of markerless lung target tracking in an experimental quality assurance procedure on a standard linear accelerator.

The ability to track tumour motion without implanted markers on a standard linear accelerator (linac) could enable wide access to real-time adaptive radiotherapy for cancer patients. We previously have retrospectively validated a method for 3D markerless target tracking using intra-fractional kilovoltage (kV) projections acquired on a standard linac. This paper presents the first prospective implementation of markerless lung target tracking on a standard linac and its quality assurance (QA) procedure. The workflow and the algorithm developed to track the 3D target position during volumetric modulated arc therapy treatment delivery were optimised. The linac was operated in clinical QA mode, while kV projections were streamed to a dedicated computer using a frame-grabber software. The markerless target tracking accuracy and precision were measured in a lung phantom experiment under the following conditions: static localisation of seven distinct positions, dynamic localisation of five patient-measured motion traces, and dynamic localisation with treatment interruption. The QA guidelines were developed following the AAPM Task Group 147 report with the requirement that the tracking margin components, the margins required to account for tracking errors, did not exceed 5 mm in any direction. The mean tracking error ranged from 0.0 to 0.9 mm (left-right), -0.6 to -0.1 mm (superior-inferior) and -0.7 to 0.1 mm (anterior-posterior) over the three tests. Larger errors were found in cases with large left-right or anterior-posterior and small superior-inferior motion. The tracking margin components did not exceed 5 mm in any direction and ranged from 0.4 to 3.2 mm (left-right), 0.7 to 1.6 mm (superior-inferior) and 0.8 to 1.5 mm (anterior-posterior). This study presents the first prospective implementation of markerless lung target tracking on a standard linac and provides a QA procedure for its safe clinical implementation, potentially enabling real-time adaptive radiotherapy for a large population of lung cancer patients.

Enhanced copper-mediated (18)F-fluorination of aryl boronic esters provides eight radiotracers for PET applications.

[(18)F]FMTEB, [(18)F]FPEB, [(18)F]flumazenil, [(18)F]DAA1106, [(18)F]MFBG, [(18)F]FDOPA, [(18)F]FMT and [(18)F]FDA are prepared from the corresponding arylboronic esters and [(18)F]KF/K222 in the presence of Cu(OTf)2py4. The method was successfully applied using three radiosynthetic platforms, and up to 26 GBq of non-carrier added starting activity of (18)F-fluoride.

Aggregation of theta-polymers in spherical confinement.

We investigate the aggregation transition of theta polymers in spherical confinement with multicanonical simulations. This allows for a systematic study of the effect of density on the aggregation transition temperature for up to 24 monodisperse polymers. Our results for solutions in the dilute regime show that polymers can be considered isolated for all temperatures larger than the aggregation temperature, which is shown to be a function of the density. The resulting competition between single-polymer collapse and aggregation yields the lower temperature bound of the isolated chain approximation. We provide entropic and energetic arguments to describe the density dependence and finite-size effects of the aggregation transition for monodisperse solutions in finite systems. This allows us to estimate the aggregation transition temperature of dilute systems in a spherical cavity, using a few simulations of small, sufficiently dilute polymer systems.